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activity (work, studies, etc.) in Germany for more than 12 months in the last 36 months Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent
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Profile: A Master’s degree in chemistry, materials science, chemical engineering, or a related field Desirable background in electrocatalysis and inorganic synthesis Fluent command of written and spoken
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via
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activity (work, studies, etc.) in Germany for more than 12 months in the last 36 months Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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of interfaces for the automated integration of research data into efficient open-source energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: Join an interdisciplinary team that brings state-of-the-art AI
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, horticulture, agriculture, completed at least with the overall grade “good” - knowledge and experience in plant cultivation under drought stress - Knowledge and experience in the phenotyping of plants
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data